BeeGass/CS-541-Deep-Learning
CS-541 Deep Learning is a graduate class that teaches both a theoretical and practical approach to deep learning. You will be able to see this in the different homework files in the form of workable code that can be tested as well as proofs and explanations as to where the code is coming from.
This is a collection of educational materials for learning deep learning, combining theoretical explanations with practical, workable code examples. It takes complex deep learning concepts and makes them accessible through hands-on assignments. Researchers, students, or professionals looking to understand and implement deep learning models would benefit from this resource.
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Use this if you are a graduate student or professional seeking to learn deep learning with a balance of theoretical understanding and practical coding exercises.
Not ideal if you are looking for a plug-and-play deep learning library for immediate application without delving into the underlying principles.
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Jupyter Notebook
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MIT
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Aug 31, 2021
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